With the explosion in the amount of new hedge funds fighting for investors, quantitative strategies are required to maintain a sustainable competitive advantage. Quantitative analysts need easy access to years of high-volume financial time series data using flexible tools to analyze the data with which integrate with their existing development environment to improve portfolio performance, understand and control risk and build and deploy competitive trading strategies. Since Quants often come from physics and mathematics backgrounds rather than finance related fields, they require complex tools to build and test data models usually using C++ as the programming language.

A large CTA Hedge Fund with $11 Billion in assets under management, required a way to conduct research on managed futures to compare historical futures data with the goal of forecasting potential performance. They needed to capture and analyze 10 years of data on to build short, medium, and long-term models, using Value-at-risk estimation, multi-factor modeling and strategy back testing. The tick capture engine needed to interface with S-Plus which is where they developed their proprietary trading models. The firm chose Velocity to uncover correlations in the historical data and build and test their trading strategies. Velocity was loaded with 10 years of data from Reuters DataScope Tick History which allowed them to create different views and analytics of the price data and retrieve all their derived data in S-Plus faster than ever before.

• Complete Velocity solution in addition to adapters for Matlab and S-Plus
• Real-time data capture and ability to query over 20 years of historical tick data in seconds
• Support Multiple Asset Classes - Equities, Fixed Income, Options and Futures
• Designed for effective back testing and strategy development
• Cost-effective and user-friendly solution that can be deployed on single desktop and includes data browser and bulk data loader
• Popular open source tools incorporated for maximum flexibility
• Equipped with Time Series language via R interface for Microsoft® Windows
• Client APIs for C++, C# and Java